# CVE-2021-29533: CHECK-fail in DrawBoundingBoxes > An attacker can cause a denial of service in TensorFlow by passing an empty image to DrawBoundingBoxes, triggering a CHECK failure and crashing the application. - **Severity:** Low 2.5 (`CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L`) - **Exploited in the wild:** Not known - **Login needed:** Any signed-in user - **Attackable:** Local or same network only - **Victim action needed:** Not needed - **Fix available:** Yes - **Published:** 14 May 2021 - **Updated:** 3 Aug 2024 - **Also known as:** BIT-tensorflow-2021-29533, GHSA-393f-2jr3-cp69, PYSEC-2021-170, PYSEC-2021-461, PYSEC-2021-659 ## What is CVE-2021-29533? CVE-2021-29533 is a low-severity denial of service vulnerability in Google Tensorflow, published on 14 May 2021. It can only be exploited from the same machine or local network, with no action from the victim. ### Official description TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a `CHECK` failure by passing an empty image to `tf.raw_ops.DrawBoundingBoxes`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/ea34a18dc3f5c8d80a40ccca1404f343b5d55f91/tensorflow/core/kernels/image/draw_bounding_box_op.cc#L148-L165) uses `CHECK_*` assertions instead of `OP_REQUIRES` to validate user controlled inputs. Whereas `OP_REQUIRES` allows returning an error condition back to the user, the `CHECK_*` macros result in a crash if the condition is false, similar to `assert`. In this case, `height` is 0 from the `images` input. This results in `max_box_row_clamp` being negative and the assertion being falsified, followed by aborting program execution. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. Weakness: CWE-754 (Improper Check for Unusual or Exceptional Conditions) ## Which versions are affected by CVE-2021-29533? 28 open source packages ship an affected version, including tensorflow, tensorflow-cpu and tensorflow-gpu. It affects 1 product. | Package | Ecosystem | Affected | Fixed in | | --- | --- | --- | --- | | `tensorflow` | Bitnami | All versions | 2.1.4, 2.2.3, 2.3.3, 2.4.2 | | `tensorflow` | PyPI | All versions | 2.2.0rc0, 2.3.0rc0, 2.3.4, 2.4.3 | | `tensorflow` | PyPI | All versions | 2.1.4 | | `tensorflow` | PyPI | All versions | 2.1.4 | | `tensorflow` | PyPI | From 2.2.0 | 2.2.3 | | `tensorflow` | PyPI | From 2.2.0 | 2.2.3 | | `tensorflow` | PyPI | From 2.3.0 | 2.3.3 | | `tensorflow` | PyPI | From 2.3.0 | 2.3.3 | | `tensorflow` | PyPI | From 2.4.0 | 2.4.2 | | `tensorflow` | PyPI | From 2.4.0 | 2.4.2 | | `tensorflow-cpu` | PyPI | All versions | 2.2.0rc0, 2.3.0rc0, 2.3.4, 2.4.3 | | `tensorflow-cpu` | PyPI | All versions | 2.1.4 | | `tensorflow-cpu` | PyPI | All versions | 2.1.4 | | `tensorflow-cpu` | PyPI | From 2.2.0 | 2.2.3 | | `tensorflow-cpu` | PyPI | From 2.2.0 | 2.2.3 | | `tensorflow-cpu` | PyPI | From 2.3.0 | 2.3.3 | | `tensorflow-cpu` | PyPI | From 2.3.0 | 2.3.3 | | `tensorflow-cpu` | PyPI | From 2.4.0 | 2.4.2 | | `tensorflow-cpu` | PyPI | From 2.4.0 | 2.4.2 | | `tensorflow-gpu` | PyPI | All versions | 2.2.0rc0, 2.3.0rc0, 2.3.4, 2.4.3 | | `tensorflow-gpu` | PyPI | All versions | 2.1.4 | | `tensorflow-gpu` | PyPI | All versions | 2.1.4 | | `tensorflow-gpu` | PyPI | From 2.2.0 | 2.2.3 | | `tensorflow-gpu` | PyPI | From 2.2.0 | 2.2.3 | | `tensorflow-gpu` | PyPI | From 2.3.0 | 2.3.3 | | `tensorflow-gpu` | PyPI | From 2.3.0 | 2.3.3 | | `tensorflow-gpu` | PyPI | From 2.4.0 | 2.4.2 | | `tensorflow-gpu` | PyPI | From 2.4.0 | 2.4.2 | Products: Google Tensorflow. ## How do I fix CVE-2021-29533? Upgrade tensorflow to a fixed version for your release line: 2.1.4, 2.2.3, 2.3.3 or 2.4.2. ## Is CVE-2021-29533 being exploited? There is no known exploitation of CVE-2021-29533 in the wild and no public exploit code. ## Other vulnerabilities in Google Tensorflow - [CVE-2023-25668](https://insights.sbomify.com/CVE-2023-25668/): TensorFlow vulnerable to heap out-of-buffer read in the QuantizeAndDequantize operation (critical 9.8) - [CVE-2018-7575](https://insights.sbomify.com/CVE-2018-7575/): Integer Overflow or Wraparound in Google TensorFlow (critical 9.8) - [CVE-2021-37678](https://insights.sbomify.com/CVE-2021-37678/): Arbitrary code execution due to YAML deserialization (critical 9.3) - [CVE-2021-35958](https://insights.sbomify.com/CVE-2021-35958/): Path traversal in n/a (critical 9.1) - [CVE-2020-15202](https://insights.sbomify.com/CVE-2020-15202/): Integer truncation in Shard API usage (critical 9.0) ## Fix prompt for AI coding agents ```text Check this codebase for CVE-2021-29533 and fix it if it is affected. What it is: CVE-2021-29533 is a low-severity denial of service vulnerability in Google Tensorflow, published on 14 May 2021. It can only be exploited from the same machine or local network, with no action from the victim. Exploitation: There is no known exploitation of CVE-2021-29533 in the wild and no public exploit code. Affected packages and fixed versions: - tensorflow (Bitnami): affected all versions; fixed in 2.1.4, 2.2.3, 2.3.3, 2.4.2 - tensorflow (PyPI): affected all versions; fixed in 2.2.0rc0, 2.3.0rc0, 2.3.4, 2.4.3 - tensorflow (PyPI): affected all versions; fixed in 2.1.4 - tensorflow (PyPI): affected all versions; fixed in 2.1.4 - tensorflow (PyPI): affected from 2.2.0; fixed in 2.2.3 - tensorflow (PyPI): affected from 2.2.0; fixed in 2.2.3 - tensorflow (PyPI): affected from 2.3.0; fixed in 2.3.3 - tensorflow (PyPI): affected from 2.3.0; fixed in 2.3.3 - tensorflow (PyPI): affected from 2.4.0; fixed in 2.4.2 - tensorflow (PyPI): affected from 2.4.0; fixed in 2.4.2 - tensorflow-cpu (PyPI): affected all versions; fixed in 2.2.0rc0, 2.3.0rc0, 2.3.4, 2.4.3 - tensorflow-cpu (PyPI): affected all versions; fixed in 2.1.4 Task: 1. Search the dependency manifests and lockfiles (for example package.json, package-lock.json, requirements.txt, poetry.lock, uv.lock, pom.xml, build.gradle, go.mod, Cargo.lock, Gemfile.lock) and any Dockerfiles for the affected packages, including transitive dependencies. 2. If an affected version is in use, upgrade it to the fixed version for its release line with the project's package manager, so the lockfile is regenerated. Prefer the smallest upgrade that fixes it. 3. If there is no fix, or the upgrade would break the build, do not guess: explain the risk and the safest workaround instead. 4. Run the tests and summarise what changed and why. 5. If nothing in the project is affected, say so and change nothing. Reference: https://insights.sbomify.com/CVE-2021-29533/ (Markdown: https://insights.sbomify.com/CVE-2021-29533/index.md) ``` ## Sources - CVE record: https://www.cve.org/CVERecord?id=CVE-2021-29533 - NVD: https://nvd.nist.gov/vuln/detail/CVE-2021-29533 - OSV: https://osv.dev/vulnerability/CVE-2021-29533 --- From sbomify Insights: https://insights.sbomify.com/CVE-2021-29533/ Summaries are generated and may contain mistakes; the official description above is the record.